A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

• git
• git-svn

$ sudo apt-get install git
$ sudo add-apt-repository ppa:git-core/ppa

A complete, reproducible walkthrough for getting both monitor mode and working packet injection out of the OnePlus 7 Pro's built-in WiFi chip (Qualcomm WCN3998, qcacld-3.0 driver) — no external USB adapter required.

This matters because the long-running XDA thread for official Kali NetHunter on the OnePlus 7 / 7 Pro has, for years, reported that the internal chip does monitor mode but injection never worked on it — the question came up repeatedly (most recently Feb 2026) with no solution, and Kali's own wireless-card docs state the same limitation. On the combination

This help only covers the parts of GLSL ES that are relevant for Shadertoy. For the complete specification please have a look at GLSL ES specification

Version: WebGL 2.0
Arithmetic: ( ) + - ! * / %
Logical/Relatonal: ~ < > <= >= == != && ||
Bit Operators: & ^ | << >>
Comments: // /* */
Types: void bool int uint float vec2 vec3 vec4 bvec2 bvec3 bvec4 ivec2 ivec3 ivec4 uvec2 uvec3 uvec4 mat2 mat3 mat4 mat?x? sampler2D, sampler3D samplerCube
Format: float a = 1.0; int b = 1; uint i = 1U; int i = 0x1;

Run two (or more) fully isolated Claude Desktop instances side by side on macOS — e.g. one signed into your personal account and one into your work account — each with its own color-coded Dock launcher that focuses the existing window instead of spawning duplicates.

This builds on Philipp Stracker's excellent --user-data-dir approach (write-up) and adds two things: